Abstract There is a great need to integrate neuroscientific tools into the study of late-life depression (LLD) etiology. My goal is to develop evidence that will help target prevention strategies to the neurobiological basis of LLD vulnerability. Several existing studies demonstrate that LLD pathophysiology is characterized a high burden of structural magnetic resonance imaging (sMRI) measured small vessel disease, white matter damage, and atrophy in key networks, such as those subserving executive and central visceral controls. To build on and extend current literature, there is a need to clarify the specific structural alterations involved in LLD pathogenesis. There is also a fundamental need for evidence regarding the preventable risk factors for pathological brain structural aging. The conceptual model that underlies my research program proposes that 24-hour sleep-wake activity disturbances are a key and understudied risk factor for the specific brain structural alterations that increase LLD risk. To lead future studies that will programmatically advance the neuroscience of depression prevention, I need to build on my past training in risk factor epidemiology and LLD neurobiology in several areas. First, I need clinical research training in the science of depression prevention for high risk older adults, such as dementia caregivers. Second, I must prepare myself to lead multi-modal, longitudinal neuroimaging studies. Third, I must prepare myself to lead studies assessing and interpreting the health relevance of 24-hour sleep-wake activity measures. Therefore, this K01 will provide me with: (1) A capstone field training experience administering ethical, multidisciplinary clinical research studies with older adults who are at high risk for developing depression, plus mentor-guided training in current LLD prevention approaches and the psychosocial/behavioral basis for LLD in at-risk groups; (2) New technical skills collecting, processing, analyzing, and interpreting multi-modal neuroimaging data, plus formal coursework in neuroanatomy/systems neurobiology, and (3) New technical skills measuring and processing 24-hour sleep-wake activity measures, plus grounding in clinical sleep medicine to interpret these metrics. To accomplish these training goals and advance public health relevant knowledge regarding LLD etiology, I propose to longitudinally study changes in depression among older informal dementia caregivers who are experiencing strain delivering care. This group is increasingly public health relevant and at very high risk for depression. Our preliminary data indicates that LLD in strained dementia caregivers may be due to disrupted brain structural connectivity. Longitudinal neuroimaging studies in this group are needed to extend our preliminary findings by evaluating whether/which specific brain structural characteristics predict future increases in the burden of depression. In addition, dementia caregivers often have inadequate sleep and restricted daytime activity, which are both depression risk factors that may increase the rate of brain structural aging (e.g., by activating pro-inflammatory cascades or contributing to vascular disease). I therefore propose a prospective study (n=90) with state-of-the-art 7- Tesla sMRI and actigraphic sleep-wake activity measures repeated at an initial visit and an 18-month follow- up. This will enable me to test and refine a model wherein specific sleep-wake activity disturbances are associated with brain structural changes affecting the key networks underlying LLD risk. The scientific and career development outcomes will be: (1) identification of the specific brain structural networks and sleep-wake activity patterns that predict increases in depression symptom severity among dementia caregivers, (2) refinement of a model linking specific sleep-wake activity characteristics with both pathological brain structural aging and depression symptoms, and (3) a multidisciplinary research scientist with the knowledge, skills, and data needed to develop a confirmatory study (R01) supporting neurobiologically-informed prevention strategies for LLD.